Analyzing Nitrogen in Silicate Glasses by Secondary Ion Mass Spectrometry
Bibliographic record
Abstract
abstract: Volcanic devolatilization is one of the major processes in the global nitrogen cycle. Past studies have often estimated the magnitude of this flux using volcanic emission measurements, which are limited to currently active systems and sensitive to atmospheric contamination. A different methodological approach requires appropriate analytical parameters for nitrogen analysis in silicate glasses by secondary ion mass spectrometry (SIMS), which have not yet been established. To this end, we analyze various ion implanted basaltic and rhyolitic glasses by SIMS. We demonstrate that water content significantly affects the ion yields of 14N+ and 14N16O−, as well as the background intensity of 14N+ and 12C+. Application of implant-derived calibrations to natural samples provide the first reported concentrations of nitrogen in melt inclusions. These measurements are from samples from the Bishop Tuff in California, the Huckleberry Ridge Tuff of the Yellowstone Volcanic Center, and material from the Okaia and Oruanui eruptions in the Taupo Volcanic Center. In all studied material, we find maximum nitrogen contents of less than 45 ppm and that nitrogen concentration varies positively with CO2 concentration, which is interpreted to reflect partial degassing trend. Using the maximum measured nitrogen contents for each eruption, we find that the Bishop released >3.6 x 1013 g of nitrogen, the Huckleberry Ridge released >1.3 x 1014 g, the Okaia released >1.1 x 1011 g of nitrogen, the Oruanui released >4.7 x 1013 g of nitrogen. Simple calculations suggest that with concentrations such as these, rhyolitic eruptions may ephemerally increase the nitrogen flux to the atmosphere, but are insignificant compared to the 4 x 1021 g of nitrogen stored in the atmosphere.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".